System and method of automatic outdoor small cell planning

ABSTRACT

A system and method for automatic deployment of at least one outdoor small cell. The method comprises dynamically collecting traffic data corresponding to a geographic location associated with a cellular network by a data collection module [ 202 ]. Next, a data collection module [ 204 ] automatically identifies a group of spatial grids from the one or more cells within the geographic location based on the traffic data and automatically determines one or more locations within the geographic locations for deploying the at least one outdoor small cell based on the identified group of spatial grids. A backhaul link clearance module [ 206 ] automatically determines a backhaul connection between the one or more determined locations with the cellular network. An azimuth planning module [ 208 ] automatically determines an azimuth for the at least one outdoor small cell based on the determined connection. A deployment unit [ 210 ] deploy the at least one outdoor small cell.

TECHNICAL FIELD

The present invention generally relates to Heterogenous Networks(HetNet) and more particularly relates to automatic deployment foroutdoor small cells for cellular networks.

BACKGROUND OF THE INVENTION

The following description of related art is intended to providebackground information pertaining to the field of the invention. Thissection may include certain aspects of the art that may be related tovarious features of the present invention. However, it should beappreciated that this section be used only to enhance the understandingof the reader with respect to the present invention, and not asadmissions of prior art.

In a traditional cellular deployment, service operators are nowreinforcing their macro-cells deployment with one or multiple lowpowered small cellular cells (generally termed as Femto/Pico/Microcells) placed at multiple strategic locations within one or more macrocoverage areas. This kind of reinforced cellular network is generallytermed as Heterogeneous Network, in short, HetNet. For a typical HetNet,strategic locations for small cells generally include areas with highdensity of users, such as shopping malls, airports, railway/busstations, colleges, etc. Also, these locations might include areas withdead-spots, or areas with low macro signal strength, such as indoorestablishments or peripheral locations of a macro coverage area. HetNetprovides increased mobile data capacity along with providing bettermobile coverage, thereby enhancing the overall user's mobile broadbandexperience.

Wi-Fi technology based on IEEE 802.11 standards has witnessed tremendousgrowth and commercialization in the recent years. Almost all theavailable user devices (or user equipment) with cellular capabilitysupport also tend to have Wi-Fi capability in order to connect to Wi-Finetworks operating in the unlicensed frequency bands, either 2.4 GHz or5 GHz. Therefore, the cellular operators are motivated to use ubiquitousand cost-effective Wi-Fi technology in pursuing the overall HetNetstrategy, for instance, deploying low powered Wi-Fi cells along withcellular small cells at multiple strategic locations identified for aHetNet. Further, for ease of maintenance and provision, few operatorsare also beginning to use Wi-Fi integrated versions of small cellularcells, wherein a Wi-Fi and cellular small cell technology are madeavailable on common equipment.

FIG. 1 illustrates an exemplary block diagram representation of aheterogenous communication network architecture [100]. Referring to FIG.1 illustrates an exemplary block diagram representation of aheterogenous communication network architecture [100], in accordancewith exemplary embodiments of the present invention. As shown in FIG. 1,the heterogenous wireless communication network [100] comprises of amacro base station [101A] wide area overlay mobility coverage, and oneor more micro base station [101B, 101C] further connected to Wi-Fiaccess points [101E, 101F, 101G, 101H, 101I], and a micro base station[101D] with built-in Wi-Fi access point capability.

Traditionally, cellular network deployment has been primarily designedfor outdoor coverage for voice services, which are achieved byovercoming the stochastic nature of the radio propagation environment.In the past decades, there have been an unprecedented growth in mobiledata demand which led to revolutions in the multiple-access technologyas well as an increase in cell density and spectrum reuse. The third,fourth and upcoming fifth generation cellular networks mostly employfull bandwidth reuse (reuse pattern one), and the cell density in urbanareas is in excess of 6 cells per square kilometer per Service Operator.This has yielded a system-level capacity that is largelyinterference-limited, as opposed to propagation-limited.

Owing to such a dense network, more than one server is generally presentin almost all the areas experiencing interference and degradation in theoverall quality of the network. Some areas may also experience poor RFquality which also degrades the network performance and deteriorates theuser experience. The Service Operators are dependent on drive testmeasurements to obtain the channel quality measurements of any area. Thedrive test measurement is very costly and time-consuming process. Inaddition to this, the drive test collects samples of outdoor areas ofthe network only whereas more than 70% of data traffic is generated fromthe indoor scenario like residential building or enterprise building.These are some drawbacks in conventional optimization methods, whichmotivated the need for a novel optimization technique.

The existing optimization techniques requires performing manual drivetest measurements and then analyzing the measurements to optimize thenetwork. The drive samples are plotted on a geographical post-processingtool to identify geographical areas poor RSRP and poor SINR. The cellsserving in that geographical area are also plotted to identify theservers in the identified geographical areas and the previous activityof these servers are studied. The cells resulting into poor quality inthe desired area are then considered for optimization and then physicalchanges are suggested which is based on an operators' defined process.Further, the drive test based conventional optimization process cannotbe made continuous process because of the unavailability of daily drivetest data. At best, the drive test optimization is periodic asconducting drive tests are cost intensive.

An existing solution provides determination of small sell location basedon usage of third-party small cell planning tool while ingestinggeolocated data. Another existing solution suggests collecting the eNBand UE data followed by decoding them for determining the small celllocation. This manual approach to identify the initial Small celllocation where processor unit will be placed and then based on thetransmission records from eNB and UE, it will take the decision ofinstalling the Small Cell. However, none of the existing solutionsprovide for small cell orientation, height determination and informationfor determining RF coverage of neighboring sites to minimizeinterference. Therefore, in view of the above highlighted and otherinherent limitations in the existing solutions, there exists a need inthe art to provide a system and a method for automatic deployment ofoutdoor small cells.

SUMMARY

This section is provided to introduce certain objects and aspects of thepresent invention in a simplified form that are further described belowin the detailed description. This summary is not intended to identifythe key features or the scope of the claimed subject matter. In order toovercome at least a few problems associated with the known solutions asprovided in the previous section, an object of the present invention isto provide a system and a method for automatic deployment of outdoorsmall cells in a geographical location. Another object of the presentinvention is to provide a system and a method for efficiently planningdeployment of outdoor small cells to improve user experience in highlycongested and poor coverage areas in an efficient and cost-effectivemanner without the requirement of manual drive test in a heterogeneousnetwork. Yet another object of the present invention is to provide asystem and a method for efficiently and effectively deploying outdoorsmall cells to improve user experience dramatically by offloading themfrom far away Macro Cells. Yet another object of the present inventionis to provide users with the enhanced experience in high density areas,such as shopping malls, airports, railway/bus stations, colleges, etc.situated within a macro coverage area. Yet another object of the presentinvention is to provide coverage in area with dead-spots, or areas withlow macro signal strength, such as indoor establishments or peripherallocations within a macro coverage area. Yet another object of thepresent invention is to provide a system and a method to provideseamless services to the users without any latency and call drops. Yetanother object of the present invention is to provide a system and amethod that facilitate cellular networks to handle high volume callsconcurrently. Yet another object of the present invention is to providea system and a method for automatic deployment of outdoor small cellthat can be used across vendors or service operators in a HeterogeneousNetwork.

In order to achieve at least some of the above-mentioned objectives, thepresent invention provides a method and system for automatic deploymentof at least one outdoor small cell in a geographic location. A firstaspect of the present invention relates to a method for automaticdeployment of at least one outdoor small cell in a geographic location.The method comprises dynamically collecting, by a data collectionmodule, a traffic data corresponding to a geographic location associatedwith a cellular network comprising of one or more cells. Next, alocation identification module automatically identifies a group ofspatial grids from the one or more cells within the geographic locationbased on the traffic data. Subsequently, the location identificationmodule automatically determines one or more locations within thegeographic locations for deploying the at least one outdoor small cellbased on the identified group of spatial grids. A backhaul linkclearance module automatically determines a backhaul connection betweenthe one or more determined locations with the cellular network. Anazimuth planning module automatically determines an azimuth for the atleast one outdoor small cell based on the determined connection. Adeployment unit deploys the at least one outdoor small cell based on atleast one of the determined one or more locations, the determinedazimuth and the determined backhaul connection.

Another aspect of the present invention relates to a system forautomatic deployment of at least one outdoor small cell in a geographiclocation. The system comprises a data collection module, a locationidentification module, a backhaul link clearance module, a deploymentunit and an azimuth planning module, all the components are connected toeach other. The data collection module is configured to collect atraffic data corresponding to a geographic location associated with acellular network comprising of one or more cells. The locationidentification module is configured to automatically identify a group ofspatial grids from the one or more cells within the geographic locationbased on the traffic data. The location identification module is alsoconfigured to automatically determine one or more locations within thegeographic locations for deploying the at least one outdoor small cellbased on the identified group of spatial grids. The backhaul linkclearance module is configured to automatically determine a backhaulconnection between the one or more determined locations with thecellular network. The azimuth planning module is configured toautomatically determine an azimuth for the at least one outdoor smallcell based on the determined connection. The deployment unit isconfigured to deploy the at least one outdoor small cell based on atleast one of the determined one or more locations, the determinedazimuth and the determined backhaul connection.

BRIEF DESCRIPTION OF DRAWINGS

The accompanying drawings, which are incorporated herein, and constitutea part of this disclosure, illustrate exemplary embodiments of thedisclosed methods and systems in which like reference numerals refer tothe same parts throughout the different drawings. Components in thedrawings are not necessarily to scale, emphasis instead being placedupon clearly illustrating the principles of the present disclosure. Somedrawings may indicate the components using block diagrams and may notrepresent the internal circuitry of each component. It will beappreciated by those skilled in the art that disclosure of such drawingsincludes disclosure of electrical components, electronic components orcircuitry commonly used to implement such components.

FIG. 1 illustrates an exemplary heterogenous network architecturediagram.

FIG. 2 illustrates an exemplary block diagram of a system for automaticdeployment of at least one outdoor small cell, in accordance withexemplary embodiments of the present invention.

FIG. 3 illustrates an exemplary Line of Sight (LOS) Clearance method forviable UBR transmission, in accordance with exemplary embodiments of thepresent invention.

FIG. 4 illustrates an exemplary block diagram of the backhaul linkclearance module [206], in accordance with exemplary embodiments of thepresent invention.

FIG. 5 illustrates an exemplary method flow diagram depicting a methodfor automatic deployment of at least one outdoor small cell, inaccordance with exemplary embodiments of the present invention.

FIG. 6 illustrates an exemplary method flow diagram depicting a methodfor automatically identification of the group of spatial grids from theone or more cells, in accordance with exemplary embodiments of thepresent invention.

FIG. 7 illustrates an exemplary method flow diagram depicting a methodfor determining the backhaul connection between the one or moredetermined locations with the cellular network, in accordance withexemplary embodiments of the present invention.

FIG. 8 illustrates an exemplary method flow diagram depicting method fordetermining the azimuth for the at least one outdoor small cell based onthe determined connection, in accordance with exemplary embodiments ofthe present invention.

FIGS. 9A and 9B (collectively referred to as FIG. 9) illustrates anexemplary implementation of the method for automatically identificationof the group of spatial grids from the one or more cells, in accordancewith exemplary embodiments of the present invention.

FIG. 10 illustrates an exemplary implementation of the method fordetermining the backhaul connection between the one or more determinedlocations with the cellular network, in accordance with exemplaryembodiments of the present invention.

FIGS. 11A, 11B and 11C (collectively referred to as FIG. 11) illustratesan exemplary implementation of the method for determining the azimuthfor the at least one outdoor small cell based on the determinedconnection, in accordance with exemplary embodiments of the presentinvention.

The foregoing shall be more apparent from the following more detaileddescription of the disclosure.

DETAILED DESCRIPTION OF THE EXEMPLARY EMBODIMENTS

In the following description, for the purposes of explanation, specificdetails are set forth in order to provide a thorough understanding ofembodiments of the invention. However, it will be apparent that variousembodiments may be practiced without these specific details. The figuresand description are not intended to be restrictive.

The ensuing description provides exemplary embodiments only, and is notintended to limit the scope, applicability, or configuration of thedisclosure. Rather, the ensuing description of the exemplary embodimentswill provide those skilled in the art with an enabling description forimplementing an exemplary embodiment. It should be understood thatvarious changes may be made in the function and arrangement of elementswithout departing from the spirit and scope of the invention as setforth.

Specific details are given in the following description to provide athorough understanding of the embodiments. However, it will beunderstood by one of ordinary skill in the art that the embodiments maybe practiced without these specific details. For example, circuits,systems, networks, processes, and other components may be shown ascomponents in block diagram form in order not to obscure the embodimentsin unnecessary detail. In other instances, well-known circuits,processes, algorithms, structures, and techniques may be shown withoutunnecessary detail in order to avoid obscuring the embodiments.

Also, it is noted that individual embodiments may be described as aprocess which is depicted as a flowchart, a flow diagram, a sequencediagram, a data flow diagram, a structure diagram, or a block diagram.Although a flowchart may describe the operations as a sequentialprocess, many of the operations can be performed in parallel orconcurrently. In addition, the order of the operations may bere-arranged. A process is terminated when its operations are completedbut could have additional steps not included in a figure. A process maycorrespond to a method, a function, a procedure, a subroutine, asubprogram, etc. When a process corresponds to a function, itstermination can correspond to a return of the function to the callingfunction or the main function.

Furthermore, embodiments may be implemented by hardware, software,firmware, middleware, microcode, hardware description languages, or anycombination thereof. When implemented in software, firmware, middlewareor microcode, the program code or code segments to perform the necessarytasks (e.g., a computer-program product) may be stored in amachine-readable medium. A processor(s) may perform the necessarytasks.’

The word “exemplary” and/or “demonstrative” is used herein to meanserving as an example, instance, or illustration. For the avoidance ofdoubt, the subject matter disclosed herein is not limited by suchexamples. In addition, any aspect or design described herein as“exemplary” and/or “demonstrative” is not necessarily to be construed aspreferred or advantageous over other aspects or designs, nor is it meantto preclude equivalent exemplary structures and techniques known tothose of ordinary skill in the art. Furthermore, to the extent that theterms “includes,” “has,” “contains,” and other similar words are used ineither the detailed description or the claims, such terms are intendedto be inclusive—in a manner similar to the term “comprising” as an opentransition word—without precluding any additional or other elements.

Reference throughout this specification to “one embodiment” or “anembodiment” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment of the present invention. Thus, theappearances of the phrases “in one embodiment” or “in an embodiment” invarious places throughout this specification are not necessarily allreferring to the same embodiment. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more embodiments.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof. As used herein, the term “and/or”includes any and all combinations of one or more of the associatedlisted items.

As utilized herein, terms “component,” “system,” “platform,” “node,”“layer,” “selector,” “interface,” and the like are intended to refer toa computer-related entity, hardware, software (e.g., in execution),and/or firmware. For example, a component can be a process running on aprocessor, a processor, an object, an executable, a program, a storagedevice, and/or a computer. By way of illustration, an applicationrunning on a server and the server can be a component. One or morecomponents can reside within a process and a component can be localizedon one computer and/or distributed between two or more computers.

Further, these components can execute from various computer-readablemedia having various data structures stored thereon. The components maycommunicate via local and/or remote processes such as in accordance witha signal having one or more data packets (e.g., data from one componentinteracting with another component in a local system, distributedsystem, and/or across a network such as the Internet with other systemsvia the signal). As another example, a component can be an apparatuswith specific functionality provided by mechanical parts operated byelectric or electronic circuitry which is operated by a softwareapplication or a firmware application executed by a processor, whereinthe processor can be internal or external to the apparatus and executesat least a part of the software or firmware application. As yet anotherexample, a component can be any apparatus that provides specificfunctionality through electronic components without mechanical parts,the electronic components can include a processor therein to executesoftware or firmware that confers at least in part the functionality ofthe electronic components.

Moreover, terms like “source and/or destination user device (UE)”,“mobile station”, “smart computing device”, “user device”, “userdevice”, “device”, “smart mobile communications device”, “mobilecommunication device”, “mobile device”, “mobile subscriber station,”“access terminal,” “terminal,” “handset,” “originating device,”“terminating device,” and similar terminology refers to any electrical,electronic, electro-mechanical computing device or equipment or acombination of one or more of the above devices. Smart computing devicesmay include, but not limited to, a mobile phone, smartphone, virtualreality (VR) devices, augmented reality (AR) devices, pager, laptop, ageneral-purpose computer, desktop, personal digital assistant, tabletcomputer, mainframe computer, or any other computing device as may beobvious to a person skilled in the art. In general, a smart computingdevice is a digital, user-configured, computer networked device that canbe operated autonomously. A smart computing device is one of theappropriate systems for storing data and other private/sensitiveinformation. The smart computing device operates at all the seven levelsof ISO reference model, but the primary function is related to theapplication layer along with the network, session and presentationlayer. The smart computing device may also have additional features of atouch screen, apps ecosystem, physical and biometric security, etc.Further, a ‘smartphone’ is one type of “smart computing device” thatrefers to the mobility wireless cellular connectivity device that allowsend users to use services on cellular networks such as including but notlimited to 2G, 3G, 4G, 5G and/or the like mobile broadband internetconnections with an advanced mobile operating system which combinesfeatures of a personal computer operating system with other featuresuseful for mobile or handheld use. These smartphones can access theInternet, have a touchscreen user interface, can run third-party appsincluding capability of hosting online applications, music players andare camera phones possessing high-speed mobile broadband 4G LTE internetwith video calling, hotspot functionality, motion sensors, mobilepayment mechanisms and enhanced security features with alarm and alertin emergencies. Mobility devices may include smartphones, wearabledevices, smart-watches, smart bands, wearable augmented devices, etc.For the sake of specificity, the mobility device is referred to bothfeature phone and smartphones in present disclosure but does not limitthe scope of the disclosure and may extend to any mobility device inimplementing the technical solutions. The above smart devices includingthe smartphone as well as the feature phone including IoT devices enablethe communication on the devices. Further, the foregoing terms areutilized interchangeably in the subject specification and relateddrawings.

Furthermore, the terms “user,” “subscriber,” “customer,” “consumer,”“owner,” and the like are employed interchangeably throughout thesubject specification and related drawings, unless context warrantsparticular distinction(s) among the terms. It should be appreciated thatsuch terms can refer to human entities, or automated componentssupported through artificial intelligence, e.g., a capacity to makeinference based on complex mathematical formulations, that can providesimulated vision, sound recognition, decision making, etc. In addition,the terms “wireless network” and “network” are used interchangeable inthe subject application, unless context warrants particulardistinction(s) among the terms.

As used herein, a “processor” or “processing unit” includes one or moreprocessors, wherein processor refers to any logic circuitry forprocessing instructions. A processor may be a general-purpose processor,a special-purpose processor, a conventional processor, a digital signalprocessor, a plurality of microprocessors, one or more microprocessorsin association with a DSP core, a controller, a microcontroller, alow-end microcontroller, Application Specific Integrated Circuits, FieldProgrammable Gate Array circuits, any other type of integrated circuits,etc. The processor may perform signal coding data processing,input/output processing, and/or any other functionality that enables theworking of the system according to the present disclosure. Morespecifically, the processor or processing unit is a hardware processor.

The present invention relates to a method and a system for automaticdeployment of at least one outdoor small cell (ODSC) in a geographiclocation. The present invention is directed to solve the problemsassociated with planning small cells based on performing manual drivetests. Thus, the solution of the present invention provides that,firstly, candidate locations are identified for outdoor small celldeployment based on the user density and poor coverage experienced byusers in the geographical location. Subsequently, the feasibility of thebackhaul link (Fiber/Microwave link) from the candidate locations to thenearest neighbor CSS site is determined. Further, a suitable azimuth forthe proposed outdoor small cells is determined such that interference tothe nearest neighbor is minimized. Accordingly, outdoor small cells aredeployed on the candidate location based on the features of the proposedsolution to improve the user experience in highly congested and poorcoverage areas in an efficient and cost-effective manner without therequirement of performing drive tests.

Hereinafter, exemplary embodiments of the present disclosure will bedescribed in detail with reference to the accompanying drawings so thatthose skilled in the art can easily carry out the present disclosure.

Referring to FIG. 2 illustrates an exemplary block diagram of a systemfor automatic deployment of at least one outdoor small cell for acellular network in a geographical location, in accordance withexemplary embodiments of the present invention. The system broadlycomprises a data collection module [202], a data collection module[204], a backhaul link clearance module [206] and an azimuth planningmodule [208], all the components are connected to each other unlessotherwise indicated and work in conjunction to achieve the objects ofthe present invention. In an instance of the present invention, thenetwork may be a wired network, a wireless network, or a combinationthereof. The network may be a single network or a combination of two ormore networks. The cellular network is responsible for providingcellular services to the user devices connected to the cellular network.

The data collection module [202] is configured to collect a traffic datacorresponding to a geographic location associated with a cellularnetwork comprising of one or more cells. The present inventionencompasses that the traffic data comprises of usage information of theusers connected to the cellular network, one or more characteristics ofthe cellular network including but not limited to Reference SignalReceive Power (RSRP).

The data collection module [204] is configured to automatically identifya group of spatial grids from the one or more cells within thegeographic location based on the traffic data. The data collectionmodule [204] is also configured to automatically determine one or morelocations within the geographic locations for deploying the at least oneoutdoor small cell based on the identified group of spatial grids.

The present invention further encompasses that the data collectionmodule [204] is further configured to extract one or more parameters forthe one or more cells of the cellular network based on the traffic datareceived at the data collection module [202], wherein the one or moreparameters comprises at least a RSRP. The data collection module [204]determines cell utilization for the each of the one or more cells. Thedata collection module [204] identifies one or more first set of spatialgrids from the one or more cells based on a comparison of the determinedcell utilization of the one or more cells with a threshold cellutilization. The data collection module [204] determines a severityvalue for each of the one or more first set of spatial grids based on anumber of sessions. The data collection module [204] identifies one ormore second set of spatial grids comprising the one or more first set ofspatial grids based on the determined severity and a centroid distanceof the one or more first set of spatial grids. The data collectionmodule [204] determines a severity value for each of the one or moresecond set of spatial grids based on a number of sessions. The datacollection module [204] selects the one or more first set of spatialgrids of the one or more second set of spatial grids based on theseverity value and the centroid distance of the one or more first set ofspatial grids. The data collection module [204] calculates a priorityscore for each of the selected one or more first set of spatial grids ofthe one or more second set of spatial grids, wherein the priority scoreis calculated based on at least a RF priority score and a transmissionpriority score. The data collection module [204] identifies one or morethird set of spatial grids as the group of spatial grids based on thecalculated priority score.

The backhaul link clearance module [206] is configured to automaticallydetermine a backhaul connection between the one or more determinedlocations with the cellular network. As also illustrated in FIG. 4, thebackhaul link clearance module [206] is further connected to a ClutterDatabase [404], a site and manhole location server [402] and a GIS MapServer [406]. The present invention further encompasses that backhaullink clearance module [206] receives one or more determined locationsfrom the data collection module [204], a fibre manhole map from the siteand manhole location server [402], a CSS site map and a GIS Map with 3Dbuilding data from the GIS Map Server [406]. The backhaul link clearancemodule [206] determines a line-of-sight (LOS) clearance and a Fresnelzone clearance between the at least one outdoor small cell and aneighboring CSS site. Referring to FIG. 3 illustrates an exemplary Lineof Sight (LOS) Clearance method for viable UBR transmission. In anexemplary instance, a Fresnel Zone is calculated using the belowequation:

$F_{n} = \sqrt{\frac{{n\lambda d}_{1}d_{2}}{d_{1} + d_{2}}}$

Where—

F_(n)=nth Fresnel Zone radius (m)d₁=distance of P from Receiver (m)d₂=distance of P from Transmitter (m)λ=wavelength of the signal (m)

In another instance, LOS clearance is assessed by calculating the first(n=1) Fresnel zone radius [306], between points A and B of the backhaullink. The Fresnel Zone is calculated for each building identified by theGIS Mapping server as intercepting a line drawn between the transmitterand receiver.

The backhaul link clearance module [206] calculates a distance betweenthe one or more determined locations and at least one neighbouringmanhole. The backhaul link clearance module [206] determines a type forthe backhaul connection between the one or more determined locations andthe cellular network based on the determined LOS clearance, thedetermined Fresnel zone clearance and the calculated distance, whereinthe type of the connection is one of a fiber connection, a microwaveconnection and a manhole connection.

The azimuth planning module [208] is configured to automaticallydetermine an azimuth for the at least one outdoor small cell based onthe determined connection. The azimuth planning module [208] receivesthe one or more determined locations for the at least one outdoor smallcell from the data collection module [204]. The azimuth planning module[208] selects a set of cells located in a vicinity of the at least oneoutdoor small cell based on a comparison of the cell utilization of theset of cells with a threshold cell utilization (for instance, toidentify highly utilized cells) wherein the set of cells face towardsthe at least one outdoor small cell. The azimuth planning module [208]calculates a bearing angle between the set of cells and the at least oneoutdoor small cell. The azimuth planning module [208] determines apreset value of the azimuth of the at least one outdoor small cell asthe bearing angle. The azimuth planning module [208] iteratively adjustsan azimuth of the at least one outdoor small cell based on a comparisonwith a calculated azimuth value, and a building height of the one ormore locations.

The system further comprises of a deployment unit [210] configured todeploy the at least one outdoor small cell based on at least one of thedetermined one or more locations, the determined azimuth and thedetermined backhaul connection. In an instance of the present invention,the deployment unit [210] comprises of physical hardware such asantennas, cables, etc. generally known to be required for deployingoutdoor small cells.

Referring to FIG. 5 illustrates an exemplary method flow diagramdepicting a method for automatic deployment of at least one outdoorsmall cell, in accordance with exemplary embodiments of the presentinvention. The method starts at step [502]. At step [504], the datacollection module [202] dynamically collects a traffic datacorresponding to a geographic location associated with a cellularnetwork comprising of one or more cells.

Subsequently, at step [506], the data collection module [204]automatically identifies a group of spatial grids from the one or morecells within the geographic location based on the traffic data. At step[508], the data collection module [204] automatically determines one ormore locations within the geographic locations for deploying the atleast one outdoor small cell based on the identified group of spatialgrids.

At step [510], the backhaul link clearance module [206] automaticallydetermines a backhaul connection between the one or more determinedlocations with the cellular network. Next, at step [512], the azimuthplanning module [208] automatically determines an azimuth for the atleast one outdoor small cell based on the determined connection. Lastly,at step [514], the method of the present invention further encompassesdeploying, by a deploying unit, the at least one outdoor small cellbased on at least one of the determined one or more locations, thedetermined azimuth and the determined backhaul connection. The methodcompletes at step [516].

The present invention encompasses that the step [506] further comprisesof steps as depicted in FIG. 6 illustrating an exemplary method flowdiagram depicting a method for automatically identification of the groupof spatial grids from the one or more cells, in accordance withexemplary embodiments of the present invention. At step [602], the datacollection module [204] extracts one or more parameters for the one ormore cells of the cellular network based on the traffic data received atthe data collection module [202], wherein the one or more parameterscomprises at least a RSRP. At step [604], the data collection module[204] determines cell utilization for the each of the one or more cells.At step [608], the data collection module [204] identifies one or morefirst set of spatial grids from the one or more cells based on acomparison of the determined cell utilization of the one or more cellswith a threshold cell utilization. At step [610], the data collectionmodule [204] determines a severity value for each of the one or morefirst set of spatial grids based on a number of sessions.

At step [612], the data collection module [204] identifies one or moresecond set of spatial grids comprising the one or more first set ofspatial grids based on the determined severity and a centroid distanceof the one or more first set of spatial grids. At step [614], the datacollection module [204] determines a severity value for each of the oneor more second set of spatial grids based on a number of sessions. Atstep [616], the data collection module [204] selects the one or morefirst set of spatial grids of the one or more second set of spatialgrids based on the severity value and the centroid distance of the oneor more first set of spatial grids. At step [618], the data collectionmodule [204] calculates a priority score for each of the selected one ormore first set of spatial grids of the one or more second set of spatialgrids, wherein the priority score is calculated based on at least a RFpriority score and a transmission priority score. Lastly, at step [620],the data collection module [204] identifies one or more third set ofcells as the group of spatial grids based on the calculated priorityscore. The method completes at step [622].

The present invention encompasses that the step [510] further comprisesof steps as depicted in FIG. 7 illustrating an exemplary method flowdiagram depicting a method for determining the backhaul connectionbetween the one or more determined locations with the cellular network,in accordance with exemplary embodiments of the present invention. Themethod starts at step [702]. At step [704], the backhaul link clearancemodule [206] receives one or more determined locations from the datacollection module [204], a fiber manhole map from site and manholelocation server [402], a CSS site map and a GIS Map with 3D buildingdata from a GIS Map Server [406]. At step [706], the backhaul linkclearance module [206] determines a line-of-sight (LOS) clearance and aFresnel zone clearance between the at least one outdoor small cell and aneighbouring CSS site. At step [708], the backhaul link clearance module[206] calculates a distance between the one or more determined locationsand at least one neighbouring manhole. Lastly, at step [710], thebackhaul link clearance module [206] determines a type for the backhaulconnection between the one or more determined locations and the cellularnetwork based on the determined LOS clearance, the determined Fresnelzone clearance and the calculated distance, wherein the type of theconnection is one of a fibre connection, a microwave connection and amanhole connection. The method completes at step [712].

The present invention encompasses that the step [512] further comprisesof steps as depicted in FIG. 8 illustrating an exemplary method flowdiagram depicting method for determining the azimuth for the at leastone outdoor small cell based on the determined connection, in accordancewith exemplary embodiments of the present invention. The methodinitiates at step [802]. At step [804], the azimuth planning module[208] receives the one or more determined locations for the at least oneoutdoor small cell from the data collection module [204]. At step [806],the azimuth planning module [208] selects a set of cells located in avicinity of the at least one outdoor small cell based on a comparison ofthe cell utilization of the set of cells with a threshold cellutilization (for instance, to identify highly utilized cells) whereinthe set of cells face towards the at least one outdoor small cell. Atstep [808], the azimuth planning module [208] calculates a bearing anglebetween the set of cells and the at least one outdoor small cell. Atstep [810], the azimuth planning module [208] determines a preset valueof the azimuth of the at least one outdoor small cell as the bearingangle. At step [812], the azimuth planning module [208] iterativelyadjusts an azimuth of the at least one outdoor small cell based on acomparison with a calculated azimuth value, and a building height of theone or more locations. The method completes at step [814].

Referring to FIG. 9 illustrates an exemplary implementation of themethod for automatically identification of the group of spatial gridsfrom the one or more cells, in accordance with exemplary embodiments ofthe present invention. The exemplary implementation of FIG. 9 alsoillustrates aspect of automatic location identification for the at leastone outdoor small cell deployment by the data collection module [204].In an instance, the present invention encompasses that the datacollection module [204] determines a group of spatial grids and one ormore location for the at least one outdoor small cell based on userdensity and poor coverage. The exemplary implementation starts at step[902].

At step [904], the data collection module [204] compiles a list of allthe highly utilized cells for each month. For instance, the datacollection module [204] extracts one or more parameters for the one ormore cells of the cellular network based on the traffic data received atthe data collection module [202], wherein the one or more parameterscomprises at least a RSRP. The data collection module [204] determinescell utilization for the each of the one or more cells and identifiesone or more first set of spatial grids as the highly utilized cells fromthe one or more cells based on a comparison of the determined cellutilization of the one or more cells with a threshold cell utilization.

At step [904], the data collection module [204] collects the geo-locatedsamples (e.g., LSR, XCAL, Net Velocity) of these highly utilized cellsmeeting the criteria, being firstly, RSRP<=−x dBm, where x is athreshold set for determining poor coverage, secondly, high confidence,and thirdly, that the highly utilized cells are within the calculatedcell range or fixed cell range as per the planning settings, e.g., “maxdistance for ODSC recommendation”. At step [908], the data collectionmodule [204] assigns the geo-located samples meeting the above criteriainto 20×20 m grids. At step [910], the data collection module [204]allocates relative severity among these 20*20 m grids based on a numberof sessions, for instance, Red: Top 75-100%, Orange: Top 50-75%, LightBlue: Top 25-50% and Dark Blue: Bottom 0-25%.

At step [912], the data collection module [204] removes the 20*20 mgrids [944] whose centroid falls within y meter, [943] of any existingor planned macro or at least one outdoor small cell, where y is thethreshold minimum distance to be maintained between any existing celland outdoor small cell. At step [914], the data collection module [204]divides the whole of the geographical location (e.g., pan India) into100 m width columns and then creates 100*100 m grids [945] covering thegreatest number of Red and Orange 20×20 m grids at step [916]. At step[918], the data collection module [204] allocates relative severityamong these 100*100 m grids in each focus town based on the number ofsessions, for instance, Red: Top 75-100%, Orange: Top 50-75%, LightBlue: Top 25-50% and Dark Blue: Bottom 0-25%. At step [920], the datacollection module [204] selects the top 75-100% grids for the at leastone outdoor small cell deployment. At step [922], the data collectionmodule [204] determines the best suitable 20*20 m child grid [946] ineach of the selected 100*100 m high severity grids by “priority logictable” as shown below in table 1.

Priority Logic Table for Best Child Grid (20*20) Selection in 100*100 mGrid Priority Max Priority Overall Overall Type Parameter CriterionWeight Score Weight Priority RF No. of Own Grid Bldg Count/Best Grid 3A*3 + 70% (RF Priority Buildings Bldg Count = A B*3 + Priority No. ofOwn Grid LMP Priority 2 C*1 + Score* Landmark Score/Best Grid LMPPriority G*2 + 0.7) + Score = A H*2 (Tx Major Own Grid Length/Best Grid1 Priority Roads Length = C Score* Unique Own Grid User Count/Best Grid2 0.3) No. of User Count = H Users No. of Own Grid Sessions Count/Best 2Sessions Grid Session Count = H Max Score 10 Tx XPIC MW LoS with any 1stTier Neighbor 3 D*3 + 30% Site CSS-XPIC MW Site (Yes = 1, E*4 + No = 0)= D F*3 Priority Fiber PoP LoS with any 1st Tier Neighbor 4 CSS-FiberSite (Yes = 1, No = 0) = E Fiber <=100 m Centroid (Yes = 1, 3 Manhole No= 0) = F Max Score 10

At step [924], the data collection module [204] determines whether theinter best child grid centroid distance is less than or equal to 80 m.In an event the inter best child grid centroid distance is less than orequal to 80 m, the method proceeds to step [926] where the datacollection module [204] creates a matrix of best child grids anddetermines their relative distances. At step [928], the data collectionmodule [204] finds the nearest child grid for the child grid in Row-1and selects the grid which has lower priority and remove its row andcolumn. At step [930], the data collection module [204] finds thenearest child grid for the child grid in row-2 and selects the gridwhich has lower priority and remove its row and column. Iteratively, atstep [932], the data collection module [204] finds the nearest childgrid for the child grid in row-N and selects the grid which has lowerpriority and remove its row and column. The method then proceeds to step[938] where an ODSC is planned at each of the identified best childgrid. Next, at step [936], a consolidated list of at least one outdoorsmall cell deployment grids is created and regularly updated with newlyidentified best child grids.

In an event the inter best child grid centroid distance is greater than80 m, the method proceeds to step [934] where at least one outdoor smallcell is planned at each of the identified best child grid. Next, at step[936], a consolidated list of at least one outdoor small cell deploymentgrids is created and regularly updated with newly identified best childgrids.

Lastly, at step [940], the data collection module [204] finds candidatebuildings with a height less than an average building height in thegrid. For instance, the data collection module [204] may determine up tothree candidate buildings with a height less than an average buildingheight in the grid. In another instance, the data collection module[204] may determine up to three candidate buildings within 5 m aboveaverage building height with exceptions such as schools, restrictedareas like defense areas, etc. The method completes at step [942].

Referring to FIG. 10 illustrates an exemplary implementation of themethod for determining the backhaul connection between the one or moredetermined locations with the cellular network, in accordance withexemplary embodiments of the present invention. The method starts atstep [1002]. At step [1004], the backhaul link clearance module [206]receives inputs such as candidate locations proposed by the datacollection module [204], the latitude and longitude details of FiberManhole from the site and manhole location server [402], CSS Site (Fiber& Microwave) locations and GIS Map of the area with 3D Building datafrom the GIS Map Server [406]. At step [1006], the backhaul linkclearance module [206] selects the at least one outdoor small celllocation proposed by the data collection module [204] for line of sight(LOS) clearance to the nearest neighboring CSS site in 1^(st) tier. Thebackhaul link clearance module [206] also checks for Fresnel Zoneclearance as highlighted in FIG. 4B. At step [1008], the backhaul linkclearance module [206] considers the below criterion for determining LOSand Fresnel clearance, firstly, height of the UBR (FT) shall beconsidered as 8 m in case of at least one outdoor small cellinstallation on pole, secondly, the UBR FT shall be considered asbuilding height+2 m in case if at least one outdoor small cell isplanned on the building, thirdly, the UBR Feeder base (FB) shall beconsidered same as the CSS site eNB antenna height and fourthly, GISdata that heights of all the buildings between at least one outdoorsmall cell site (FT) and CSS site (FB).

In an event the LOS and Fresnel Zone clearance is successful, thebackhaul link clearance module [206] discards the link at step [1010]and proceeds to step [1012] for checking LOS clearance to next (second)nearest neighboring CSS site in the 1^(st) tier. In an event the LOSclearance is successful, the backhaul link clearance module [206]proceeds to step [1024], otherwise the backhaul link clearance module[206] discards the link at step [1014] and proceeds to step [1016] forchecking LOS clearance to next (third) nearest neighboring CSS site inthe 1^(st) tier. In an event the LOS clearance is successful, thebackhaul link clearance module [206] proceeds to step [1024], otherwisethe backhaul link clearance module [206] iteratively discards the linkat step [1018] and proceeds to step [1020] for checking LOS clearance tonext (Nth) nearest neighboring CSS site in the 1^(st) tier untilLOS/Fresnel Zone is clear or verification is completed with all theneighbors in 1^(st) tier. In an event the LOS clearance is successful,the backhaul link clearance module [206] proceeds to step [1024],otherwise the backhaul link clearance module [206] determines that theUBR is not feasible for the candidate at least one outdoor small celllocation.

In an event the LOS and Fresnel Zone clearance is successful at step[1006], the backhaul link clearance module [206] checks for backhaulavailability at the CSS site at step [1024]. At step [1024], thebackhaul link clearance module [206] determines if CSS site has FiberPoP. In an event the CSS site has Fiber PoP, the backhaul link clearancemodule [206] finalizes the UBR link between ODSC (FT) site to CSS FiberPoP at step [1026], and the method completes at step [1040]. In an eventthe backhaul link clearance module [206] determines that the CSS sitehas no Fiber PoP, the backhaul link clearance module [206] determineswhether the CSS site has Microwave with 2+0 (XPIC) configurable radio atstep [1028]. In an event the CSS site has Microwave with 2+0 (XPIC)configurable radio, the backhaul link clearance module [206] determinesUnlicensed Band Radio (UBR) link between ODSC (FT) site to CSS-Fiber(FB)/CSS-MW (FB) back to Outdoor small cell planner at step [1036], andthereafter the method completes at step [1040].

At step [108], in an event neither Fiber PoP nor Microwave with 2+0(XPIC) is available at CSS site, the backhaul link clearance module[206] measures the distance between at least one outdoor small cell siteand nearest manhole location at step [1030]. At step [1032], if themeasured distance is within d_(m) meters, where d_(m) is the maximumdistance to be maintained between a planned outdoor small cell andmanhole, the backhaul link clearance module [206] suggests using manholefor providing backhaul solution to at least one outdoor small cell,otherwise the backhaul link clearance module [206] discards the link andreport backhaul not possible in case of more than d_(m) meters distanceat step [1038]. The method completes at step [1040].

Referring to FIG. 11 illustrates an exemplary implementation of themethod for determining the azimuth for the at least one outdoor smallcell based on the determined connection, in accordance with exemplaryembodiments of the present invention. The method starts at step [1102].At step [1104], the azimuth planning module [208] receives as inputs thelist of highly utilized cells along with their Congestion Class details,Morphology and Building Database, Landmarks and their Priority, at leastone outdoor small cell candidate/location list (C1, C2 and C3) from thedata collection module [204]. At step [1106], the azimuth planningmodule [208] obtains list of at least one outdoor small cell CandidateLocations as per Feasibility Report. At step [1108], the azimuthplanning module [208] determines the Tier 1 Highly Utilized Cells forOSDC Candidate Locations.

At step [1108], the azimuth planning module [208] selects the HighlyUtilized cells facing towards the at least one outdoor small celllocation, say, with an azimuth within +−45 deg of bearing angle. At step[1108], the azimuth planning module [208] arranges such Highly utilizedcells in the order their congestion from high to low. Considering ‘n’ isthe number of highly utilized cells and start with a variable “m” equalto 1 and an “ODSC-count” equal to zero, the azimuth planning module[208] finds the azimuth (bearing angle) from at least one outdoor smallcell location to first Highly utilized cell in the list in steps[1116-1120].

At step [1122], the azimuth planning module [208] check if any otherhighly utilized cells appear within +−75 deg of azimuth and calculates acenter azimuth of all such cells at step [1124]. At step [1126], theazimuth planning module [208] removes the additional cells from theselected Highly utilized cells list for this at least one outdoor smallcell location, at step [1128] recalculates n as n minus (−) no. ofadditional cells within +−75 deg of azimuth. Further, at step [1160],the azimuth planning module [208] checks average building height in anarc of +−30 deg span of the azimuth within 60 m distance from at leastone outdoor small cell location. At step [1162], the azimuth planningmodule [208] determines whether average height is less than or equal toat least one outdoor small cell building height. In event the averageheight is less than or equal to at least one outdoor small cell buildingheight, the azimuth planning module [208] plans at least one outdoorsmall cell at the determined azimuth at step [1164].

In an event the azimuth planning module [208] determines that theaverage height is greater than the at least one outdoor small cellbuilding height, at step [1170], the azimuth planning module [208]changes the original azimuth by +15 and further determines if theaverage height is less than or equal to at least one outdoor small cellbuilding height at step [1172]. In an event the azimuth planning module[208] finds that the average height is less than or equal to at leastone outdoor small cell building height at step [1172], the methodproceeds to step [1164] the azimuth planning module [208] plans at leastone outdoor small cell at the determined azimuth. In an event, theazimuth planning module [208] finds that the average height is greaterthan the at least one outdoor small cell building height at step [1172],the azimuth planning module [208] changes the original azimuth by −15 atstep [1174] and further determines if the average height is less than orequal to at least one outdoor small cell building height at step [1176].Accordingly, in event the average height is less than or equal to atleast one outdoor small cell building height, the method proceeds tostep [1164] the azimuth planning module [208] plans at least one outdoorsmall cell at the determined azimuth, otherwise the azimuth planningmodule [208] sets the status for the at least one outdoor small cellcandidate location as “field audit required” in the report and increment‘m’ and ‘ODSC-count’ by one at steps [1180 and 1182], and methodthereafter proceeds to step [1116]. Accordingly, after step [1164], theazimuth planning module [208] increments ‘m’ and the ‘ODSC-count’ byone, and method thereafter proceeds to step [1116].

At step [1116], the azimuth planning module [208] checks for thecondition ‘m<n’. If satisfied, at step [1118], the azimuth planningmodule [208] checks for the condition ‘ODSC-count<3’. The azimuthplanning module [208] then finds azimuth from at least one outdoor smallcell location to next highly utilized cell in the list and repeat thesame procedure from step [1112] when ‘true’ as above, and directlyproceed to step [1160] when ‘false’. However, if the condition ‘m<n’ isnot satisfied at step [1116], the azimuth planning module [208] checksfor the condition ‘ODSC-count<3’ at step [1130]. The azimuth planningmodule [208] then checks for the condition ‘ODSC-count=2’ at step[1132]. If the condition ‘ODSC-count=2’ is true, then the methodproceeds to step [1134] for calculating clockwise difference (D) betweentwo planned azimuths (A1 and A2).

At step [1136], the azimuth planning module [208] calculates a value ofD and determines whether one of the conditions exists 160<D<=200 degreesor D>200 degrees or D<=160 degrees. If 160<D<=200 degrees, the methodproceeds to step [1146] to find center azimuth (CA) between A1 and A2.Further, the method comprises calculating A3_1=CA+−20 deg based onlandmark priority (for landmarks within 60 m) and A3_2=CA+−180 deg basedon landmark priority (for landmarks within 60 m) at step [1148]. At step[1150], the azimuth planning module [208] determines the third at leastone outdoor small cell azimuth (A3)=best of A3_1 and A3_2 (based onlandmark priority for landmarks within 60 m). The method thereafterproceeds to step [1184] where the azimuth for OSDC cell is updated inthe consolidated list.

At step [1136], if D>200 degrees, the method proceeds to step [1142] tofind center azimuth (CA) between A1 and A2, and to calculate a third atleast one outdoor small cell azimuth (A3)=CA+−20 deg (based on landmarkpriority for landmarks within 60 m) at step [1144]. The methodthereafter proceeds to step [1184] where the azimuth for OSDC cell isupdated in the consolidated list and completes at step [1186].

At step [1136], if D<=160 degrees, the method proceeds to step [1138] tofind center azimuth (CA) between A1 and A2 and to calculate a third atleast one outdoor small cell azimuth (A3)=(CA+180)+−20 deg (based onlandmark priority for landmarks within 60 m) at step [1140]. The methodthereafter proceeds to step [1184] where the azimuth for OSDC cell isupdated in the consolidated list and completes at step [1186].

However, if the condition ‘ODSC-count=2’ is not true at step [1132], theazimuth planning module [208] checks for the condition ‘ODSC-count=1’ atstep [1152]. If the condition is true, the azimuth planning module [208]finds new possible azimuths at step [1156] and calculatesA2=(A1+120)+−30 deg based on landmark priority (for landmarks within 60m) and A3=(A1−120)+−30 deg based on landmark priority (for landmarkswithin 60 m) at step [1158] and determines a second ODSC azimuth=best ofA2 and A3 (based on landmark priority for landmarks within 60 m). Themethod thereafter proceeds to step [1184] where the azimuth for OSDCcell is updated in the consolidated list and completes at step [1186].At step [1152], if the condition is false, the azimuth planning module[208] proceeds to step [1154] to find Azimuth for next at least oneoutdoor small cell Candidate Location and the method proceeds asdescribed above.

The novel solution of the present invention provides a system and amethod for automatic deployment of outdoor small cells in a geographicallocation to solve the problem of deployment in highly congested and poorcoverage areas in an efficient and cost-effective manner without therequirement of performing manual drive tests in a heterogeneous network.Thus, the present invention provides for deploying outdoor small cellsto improve user experience dramatically by offloading them from far awaymacro cells and facilitates cellular networks to handle high volumecalls concurrently.

While considerable emphasis has been placed herein on the preferredembodiments, it will be appreciated that many embodiments can be madeand that many changes can be made in the preferred embodiments withoutdeparting from the principles of the invention. These and other changesin the preferred embodiments of the invention will be apparent to thoseskilled in the art from the invention herein, whereby it is to bedistinctly understood that the foregoing descriptive matter to beimplemented merely as illustrative of the invention and not aslimitation.

We claim:
 1. A method for automatic deployment of at least one outdoorsmall cell in a geographic location, the method comprising: dynamicallycollecting, by a data collection module [202], a traffic datacorresponding to a geographic location associated with a cellularnetwork comprising of one or more cells; identifying, by a datacollection module [204], a group of spatial grids from the one or morecells within the geographic location based on the traffic data;determining, by the data collection module [204], one or more locationswithin the geographic locations for deploying the at least one outdoorsmall cell based on the identified group of spatial grids; determining,by a backhaul link clearance module [206], a backhaul connection betweenthe one or more determined locations with the cellular network;determining, by an azimuth planning module [208], an azimuth for the atleast one outdoor small cell based on the determined connection; anddeploying, by a deployment unit [210], the at least one outdoor smallcell based on at least one of the determined one or more locations, thedetermined azimuth and the determined backhaul connection.
 2. The methodas claimed in claim 1, wherein automatically identifying, by the datacollection module [204], the group of spatial grids from the one or morecells further comprises: extracting one or more parameters for the oneor more cells of the cellular network based on the traffic data receivedat the data collection module [202], wherein the one or more parameterscomprises at least RSRP determining cell utilization for the each of theone or more cells; identifying one or more first set of spatial gridsfrom the one or more cells based on a comparison of the determined cellutilization of the one or more cells with a threshold cell utilization;determining a severity value for each of the one or more first set ofspatial grids based on a number of sessions; identifying one or moresecond set of spatial grids comprising the one or more first set ofspatial grids based on the determined severity and a centroid distanceof the one or more first set of spatial grids; determining a severityvalue for each of the one or more second set of spatial grids based on anumber of sessions; selecting the one or more first set of spatial gridsof the one or more second set of spatial grids based on the severityvalue and the centroid distance of the one or more first set of spatialgrids; calculating a priority score for each of the selected one or morefirst set of spatial grids of the one or more second set of spatialgrids, wherein the priority score is calculated based on at least a RFpriority score and a transmission priority score; and identifying one ormore third set of cells as the group of spatial grids based on thecalculated priority score.
 3. The method as claimed in claim 1, whereinthe determining the backhaul connection between the one or moredetermined locations with the cellular network by the backhaul linkclearance module [206] further comprises: receiving one or moredetermined locations from the data collection module [204], a fibremanhole map from site and manhole location server [402], a CSS site mapand a GIS Map with 3D building data from a GIS Map Server [406];determining a line-of-sight (LOS) clearance and a Fresnel zone clearancebetween the at least one outdoor small cell and a neighbouring CSS site;calculating a distance between the one or more determined locations andat least one neighbouring manhole; and determining a type for thebackhaul connection between the one or more determined locations and thecellular network based on the determined LOS clearance, the determinedFresnel zone clearance and the calculated distance, wherein the type ofthe connection is one of a fibre connection, a microwave connection anda manhole connection.
 4. The method as claimed in claim 1, whereindetermining the azimuth for the at least one outdoor small cell based onthe determined connection by the azimuth planning module [208] furthercomprises: receiving the one or more determined locations for the atleast one outdoor small cell from the data collection module [204];selecting a set of cells located in a vicinity of the at least oneoutdoor small cell based on a comparison of the cell utilization of theset of cells with a threshold cell utilization wherein the set of cellsface towards the at least one outdoor small cell; calculating a bearingangle between set of cells and the at least one outdoor small cell;determining a preset value of the azimuth of the at least one outdoorsmall cell as the bearing angle; and iteratively adjusting an azimuth ofthe at least one outdoor small cell based on a comparison with acalculated azimuth value, and a building height of the one or morelocations.
 5. A system for automatic deployment of at least one outdoorsmall cell in a geographic location, the system comprising: a datacollection module [202] configured to dynamically collect a traffic datacorresponding to a geographic location associated with a cellularnetwork comprising of one or more cells; a data collection module [204]connected to the data collection module [202], said data collectionmodule [204] configured to: automatically identify a group of spatialgrids from the one or more cells within the geographic location based onthe traffic data, and automatically determine one or more locationswithin the geographic locations for deploying the at least one outdoorsmall cell based on the identified group of spatial grids; a backhaullink clearance module [206] connected to the data collection module[204] and the data collection module [202], said backhaul link clearancemodule [206] configured to automatically determine a backhaul connectionbetween the one or more determined locations with the cellular network;and an azimuth planning module [208] connected to the backhaul linkclearance module [206], the data collection module [204] and the datacollection module [202], said azimuth planning module [208] configuredto automatically determine an azimuth for the at least one outdoor smallcell based on the determined connection; and a deployment unit [210]connected to the azimuth planning module [208], the backhaul linkclearance module [206], the data collection module [204] and the datacollection module [202], said deployment unit [210] configured to deploythe at least one outdoor small cell based on at least one of thedetermined one or more locations, the determined azimuth and thedetermined backhaul connection
 6. The system as claimed in claim 5,wherein the data collection module [204] is further configured to:extract one or more parameters for the one or more cells of the cellularnetwork based on the traffic data received at the data collection module[202], wherein the one or more parameters comprises at least a RSRP;determine cell utilization for the each of the one or more cells;identify one or more first set of spatial grids from the one or morecells based on a comparison of the determined cell utilization of theone or more cells with a threshold cell utilization; determine aseverity value for each of the one or more first set of spatial gridsbased on a number of sessions; identify one or more second set of gridscomprising the one or more first set of spatial grids based on thedetermined severity and a centroid distance of the one or more first setof spatial grids; determine a severity value for each of the one or moresecond set of spatial grids based on a number of sessions; select theone or more first set of grids of the one or more second set of spatialgrids based on the severity value and the centroid distance of the oneor more first set of spatial grids; calculate a priority score for eachof the selected one or more first set of spatial grids of the one ormore second set of spatial grids, wherein the priority score iscalculated based on at least a RF priority score and a transmissionpriority score; and identify one or more third set of cells as the groupof spatial grids based on the calculated priority score.
 7. The systemas claimed in claim 5, wherein the backhaul link clearance module [206]is further configured to: receive one or more determined locations fromthe data collection module [204], a fibre manhole map from site andmanhole location server [402], a CSS site map and a GIS Map with 3Dbuilding data from a GIS Map Server [406]; determine a line-of-sight(LOS) clearance and a Fresnel zone clearance between the at least oneoutdoor small cell and a neighbouring CSS site; calculate a distancebetween the one or more determined locations and at least oneneighbouring manhole; and determine a type for the backhaul connectionbetween the one or more determined locations and the cellular networkbased on the determined LOS clearance, the determined Fresnel zoneclearance and the calculated distance, wherein the type of theconnection is one of a fibre connection, a microwave connection and amanhole connection.
 8. The method as claimed in claim 5, wherein theazimuth planning module [208] is further configured to: receive the oneor more determined locations for the at least one outdoor small cellfrom the data collection module [204]; select a set of cells located ina vicinity of the at least one outdoor small cell based on a comparisonof the cell utilization of the set of cells with a threshold cellutilization wherein the set of cells face towards the at least oneoutdoor small cell; calculate a bearing angle between the set of cellsand the at least one outdoor small cell; determine a preset value of theazimuth of the at least one outdoor small cell as the bearing angle; anditeratively adjust an azimuth of the at least one outdoor small cellbased on a comparison with a calculated azimuth value, and a buildingheight of the one or more locations.